Numerical Implementation and Computer Simulation of Tracer Experiments in a Physical Aquifer Model

The numerical model Sand Model was developed and used to replicate the laboratory sand tank model. The plots of the TBCs for the twelve (12) multilevel observation points within the model domain show a reasonable match of the simulated and observed tracer breakthrough curves. The calculated t value (Paired-t test statistic) for each well is less than the critical value of t ( tcritical = 2.16 for df=13), and the calculated P value for each well is greater than the chosen significance level (P=0.05), therefore the null (no difference) between observed and simulated data sets hypothesis is accepted. The analysis also reveals high to very high correlation between the observed and simulated values (Average R2 = 0.86). It took eight (8) and Twelve (12) hours respectively for the tracer to reach its peak concentrations of 3.81mS/cm and 1.55mS/cm respectively for the middle (observation point (BM) [x,y,z] [70,15,24] and down gradient observation point (EM) [x,y,z] [30,15,24] within the sand tank model. A sensitivity analysis showed that the time required for complete source depletion, was most dependent on the source definition and the hydraulic conductivity K of the porous medium. The 12000mg/l chloride tracer source was almost completely dispersed within 34 hours.Keywords: Replication, Numerical simulation, Model validation, Solutetransport parameters, Tropical soi

Custom-designed orthopedic implants evaluated using finite element analysis of patient-specific computed tomography data: femoral-component case study

<p>Abstract</p> <p>Background</p> <p>Conventional knee and hip implant systems have been in use for many years with good success. However, the custom design of implant components based on patient-specific anatomy has been attempted to overcome existing shortcomings of current designs. The longevity of cementless implant components is highly dependent on the initial fit between the bone surface and the implant. The bone-implant interface design has historically been limited by the surgical tools and cutting guides available; and the cost of fabricating custom-designed implant components has been prohibitive.</p> <p>Methods</p> <p>This paper describes an approach where the custom design is based on a Computed Tomography scan of the patient's joint. The proposed design will customize both the articulating surface and the bone-implant interface to address the most common problems found with conventional knee-implant components. Finite Element Analysis is used to evaluate and compare the proposed design of a custom femoral component with a conventional design.</p> <p>Results</p> <p>The proposed design shows a more even stress distribution on the bone-implant interface surface, which will reduce the uneven bone remodeling that can lead to premature loosening.</p> <p>Conclusion</p> <p>The proposed custom femoral component design has the following advantages compared with a conventional femoral component. (i) Since the articulating surface closely mimics the shape of the distal femur, there is no need for resurfacing of the patella or gait change. (ii) Owing to the resulting stress distribution, bone remodeling is even and the risk of premature loosening might be reduced. (iii) Because the bone-implant interface can accommodate anatomical abnormalities at the distal femur, the need for surgical interventions and fitting of filler components is reduced. (iv) Given that the bone-implant interface is customized, about 40% less bone must be removed. The primary disadvantages are the time and cost required for the design and the possible need for a surgical robot to perform the bone resection. Some of these disadvantages may be eliminated by the use of rapid prototyping technologies, especially the use of Electron Beam Melting technology for quick and economical fabrication of custom implant components.</p

Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes.

INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates. RESULTS: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB. CONCLUSION: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study

Long Lasting Local and Systemic Inflammation after Cerebral Hypoxic ischemia in Newborn Mice

Background: Hypoxic ischemia (HI) is an important cause of neonatal brain injury and subsequent inflammation affects neurological outcome. In this study we performed investigations of systemic and local activation states of inflammatory cells from innate and adaptive immunity at different time points after neonatal HI brain injury in mice. Methodology/Principal Findings: We developed a multiplex flow cytometry based method combined with immunohistochemistry to investigate cellular immune responses in the brain 24 h to 7 months after HI brain injury. In addition, functional studies of ex vivo splenocytes after cerebral hypoxic ischemia were performed. Both central and peripheral activation of CD11b + and CD11c + antigen presenting cells were seen with expression of the costimulatory molecule CD86 and MHC-II, indicating active antigen presentation in the damaged hemisphere and in the spleen. After one week, naïve CD45rb + T-lymphocytes were demonstrated in the damaged brain hemisphere. In a second phase after three months, pronounced activation of CD45rb 2 T-lymphocytes expressing CD69 and CD25 was seen in the damaged hemisphere. Brain homogenate induced proliferation in splenocytes after HI but not in controls. Conclusions/Significance: Our findings demonstrate activation of both local and systemic immune responses months after hypoxic ischemic neonatal brain injury. The long term immune activation observed is of general importance for future studies of the inflammatory response after brain injury as most previous studies have focused on the first few weeks afte

Ejection Time-Corrected Systolic Velocity Improves Accuracy in the Evaluation of Myocardial Dysfunction: A Study in Piglets

This study aimed to assess the effect of correcting for the impact of heart rate (HR) or ejection time (ET) on myocardial velocities in the long axis in piglets undergoing hypoxia. The ability to eject a higher volume at a fixed ET is a characteristic of contractility in the heart. Systolic velocity of the atrioventricular annulus displacement is directly related to volume changes of the ventricle. Both ET and systolic velocity may be measured in a single heartbeat. In 29 neonatal pigs, systolic velocity and ET were measured with tissue Doppler techniques in the mitral valve annulus, the tricuspid valve annulus, and the septum. All ejection time corrected velocities (S(ET), mean ± SEM, cm/s) decreased significantly during hypoxia (Smva(ET) 15.5 ± 0.2 to 13.2 ± 0.3 (p < 0.001), Sseptal(ET) 9.9 ± 0.1 to 7.8 ± 0.2 (p < 0.001), Stva(ET) 12.1 ± 0.2 to 9.8 ± 0.3 (p < 0.001)). The magnitude of change from baseline to hypoxia was greater for ejection time corrected systolic velocities than for RR-interval corrected velocities (mean ± SEM, cm/s); ΔSmva(ET) 2.3 ± 2.0 vs. ΔSmva(RR) 1.6 ± 1.1 (p = 0.02), ΔSseptal(ET) 2.1 ± 1.0 vs. ΔSseptal(RR) 1.6 ± 1.0 (p < 0.01), ΔStva(ET) 2.3 ± 1.1 vs. ΔStva(RR) 1.8 ± 1.3 (p = 0.04). The receiver operator characteristic (ROC) showed superior performance of S(ET) compared with uncorrected velocities. The decrease in S(ET) during hypoxia was not influenced by important hemodynamic determinants. ET-corrected systolic velocity improves accuracy and decreases variability in the evaluation of systolic longitudinal function and contractility during global hypoxia in neonatal pigs compared with systolic velocity alone. It is robust toward hemodynamic changes. This novel method has the potential of becoming a useful tool in clinical practice

LPS Regulates SOCS2 Transcription in a Type I Interferon Dependent Autocrine-Paracrine Loop

Recent studies suggest that SOCS2 is involved in the regulation of TLR signaling. In this study, we found that the expression of SOCS2 is regulated in human monocyte-derived DC by ligands stimulating TLR2, 3, 4, 5, 8 and 9 signaling. SOCS2 induction by LPS was dependent on the type I IFN regulated transcription factors IRF1 and IRF3 as shown by using silencing RNAs for IRFs. Blocking endogenous type I IFN signaling, by neutralizing antibodies to the receptor IFNAR2, abolished SOCS2 mRNA expression after TLR4 stimulation. Transcription factors STAT3, 5 and 6 displayed putative binding sites in the promoter regions of the human SOCS2 gene. Subsequent silencing experiments further supported that STAT3 and STAT5 are involved in LPS induced SOCS2 regulation. In mice we show that SOCS2 mRNA induction is 45% lower in bone marrow derived macrophages derived from MyD88−/− mice, and do not increase in BMMs from IRF3−/− mice after BCG infection. In conclusion, our results suggest that TLR4 signaling indirectly increases SOCS2 in late phase mainly via the production of endogenous type I IFN, and that subsequent IFN receptor signaling activates SOCS2 via STAT3 and STAT5

Role of 3′UTRs in the Translation of mRNAs Regulated by Oncogenic eIF4E—A Computational Inference

Eukaryotic cap-dependent mRNA translation is mediated by the initiation factor eIF4E, which binds mRNAs and stimulates efficient translation initiation. eIF4E is often overexpressed in human cancers. To elucidate the molecular signature of eIF4E target mRNAs, we analyzed sequence and structural properties of two independently derived polyribosome recruited mRNA datasets. These datasets originate from studies of mRNAs that are actively being translated in response to cells over-expressing eIF4E or cells with an activated oncogenic AKT: eIF4E signaling pathway, respectively. Comparison of eIF4E target mRNAs to mRNAs insensitive to eIF4E-regulation has revealed surprising features in mRNA secondary structure, length and microRNA-binding properties. Fold-changes (the relative change in recruitment of an mRNA to actively translating polyribosomal complexes in response to eIF4E overexpression or AKT upregulation) are positively correlated with mRNA G+C content and negatively correlated with total and 3′UTR length of the mRNAs. A machine learning approach for predicting the fold change was created. Interesting tendencies of secondary structure stability are found near the start codon and at the beginning of the 3′UTR region. Highly upregulated mRNAs show negative selection (site avoidance) for binding sites of several microRNAs. These results are consistent with the emerging model of regulation of mRNA translation through a dynamic balance between translation initiation at the 5′UTR and microRNA binding at the 3′UTR